#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import cProfile
import pstats
import os
import atexit
from pyspark.accumulators import AccumulatorParam
class ProfilerCollector(object):
"""
This class keeps track of different profilers on a per
stage basis. Also this is used to create new profilers for
the different stages.
"""
def __init__(self, profiler_cls, dump_path=None):
self.profiler_cls = profiler_cls
self.profile_dump_path = dump_path
self.profilers = []
def new_profiler(self, ctx):
""" Create a new profiler using class `profiler_cls` """
return self.profiler_cls(ctx)
def add_profiler(self, id, profiler):
""" Add a profiler for RDD `id` """
if not self.profilers:
if self.profile_dump_path:
atexit.register(self.dump_profiles, self.profile_dump_path)
else:
atexit.register(self.show_profiles)
self.profilers.append([id, profiler, False])
def dump_profiles(self, path):
""" Dump the profile stats into directory `path` """
for id, profiler, _ in self.profilers:
profiler.dump(id, path)
self.profilers = []
def show_profiles(self):
""" Print the profile stats to stdout """
for i, (id, profiler, showed) in enumerate(self.profilers):
if not showed and profiler:
profiler.show(id)
# mark it as showed
self.profilers[i][2] = True
class Profiler(object):
"""
.. note:: DeveloperApi
PySpark supports custom profilers, this is to allow for different profilers to
be used as well as outputting to different formats than what is provided in the
BasicProfiler.
A custom profiler has to define or inherit the following methods:
profile - will produce a system profile of some sort.
stats - return the collected stats.
dump - dumps the profiles to a path
add - adds a profile to the existing accumulated profile
The profiler class is chosen when creating a SparkContext
>>> from pyspark import SparkConf, SparkContext
>>> from pyspark import BasicProfiler
>>> class MyCustomProfiler(BasicProfiler):
... def show(self, id):
... print("My custom profiles for RDD:%s" % id)
...
>>> conf = SparkConf().set("spark.python.profile", "true")
>>> sc = SparkContext('local', 'test', conf=conf, profiler_cls=MyCustomProfiler)
>>> sc.parallelize(range(1000)).map(lambda x: 2 * x).take(10)
[0, 2, 4, 6, 8, 10, 12, 14, 16, 18]
>>> sc.parallelize(range(1000)).count()
1000
>>> sc.show_profiles()
My custom profiles for RDD:1
My custom profiles for RDD:3
>>> sc.stop()
"""
def __init__(self, ctx):
pass
def profile(self, func):
""" Do profiling on the function `func`"""
raise NotImplemented
def stats(self):
""" Return the collected profiling stats (pstats.Stats)"""
raise NotImplemented
def show(self, id):
""" Print the profile stats to stdout, id is the RDD id """
stats = self.stats()
if stats:
print("=" * 60)
print("Profile of RDD<id=%d>" % id)
print("=" * 60)
stats.sort_stats("time", "cumulative").print_stats()
def dump(self, id, path):
""" Dump the profile into path, id is the RDD id """
if not os.path.exists(path):
os.makedirs(path)
stats = self.stats()
if stats:
p = os.path.join(path, "rdd_%d.pstats" % id)
stats.dump_stats(p)
class PStatsParam(AccumulatorParam):
"""PStatsParam is used to merge pstats.Stats"""
@staticmethod
def zero(value):
return None
@staticmethod
def addInPlace(value1, value2):
if value1 is None:
return value2
value1.add(value2)
return value1
class BasicProfiler(Profiler):
"""
BasicProfiler is the default profiler, which is implemented based on
cProfile and Accumulator
"""
def __init__(self, ctx):
Profiler.__init__(self, ctx)
# Creates a new accumulator for combining the profiles of different
# partitions of a stage
self._accumulator = ctx.accumulator(None, PStatsParam)
def profile(self, func):
""" Runs and profiles the method to_profile passed in. A profile object is returned. """
pr = cProfile.Profile()
pr.runcall(func)
st = pstats.Stats(pr)
st.stream = None # make it picklable
st.strip_dirs()
# Adds a new profile to the existing accumulated value
self._accumulator.add(st)
def stats(self):
return self._accumulator.value
if __name__ == "__main__":
import doctest
(failure_count, test_count) = doctest.testmod()
if failure_count:
exit(-1)
